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Path analyses of cross-sectional and longitudinal data suggest that variability in natural communities of blood-associated parasites is derived from host characteristics and not interspecific…

Overview of attention for article published in Parasites & Vectors, August 2015
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Title
Path analyses of cross-sectional and longitudinal data suggest that variability in natural communities of blood-associated parasites is derived from host characteristics and not interspecific interactions
Published in
Parasites & Vectors, August 2015
DOI 10.1186/s13071-015-1029-5
Pubmed ID
Authors

Carmit Cohen, Monica Einav, Hadas Hawlena

Abstract

The parasite composition of wild host individuals often impacts their behavior and physiology, and the transmission dynamics of pathogenic species thereby determines disease risk in natural communities. Yet, the determinants of parasite composition in natural communities are still obscure. In particular, three fundamental questions remain open: (1) what are the relative roles of host and environmental characteristics compared with direct interactions between parasites in determining the community composition of parasites? (2) do these determinants affect parasites belonging to the same guild and those belonging to different guilds in similar manners? and (3) can cross-sectional and longitudinal analyses work interchangeably in detecting community determinants? Our study was designed to answer these three questions in a natural community of rodents and their fleas, ticks, and two vector-borne bacteria. We sampled a natural population of Gerbillus andersoni rodents and their blood-associated parasites on two occasions. By combining path analysis and model selection approaches, we then explored multiple direct and indirect paths that connect (i) the environmental and host-related characteristics to the infection probability of a host by each of the four parasite species, and (ii) the infection probabilities of the four species by each other. Our results suggest that the majority of paths shaping the blood-associated communities are indirect, mostly determined by host characteristics and not by interspecific interactions or environmental conditions. The exact effects of host characteristics on infection probability by a given parasite depend on its life history and on the method of sampling, in which the cross-sectional and longitudinal methods are complementary. Despite the awareness of the need of ecological investigations into natural host-vector-parasite communities in light of the emergence and re-emergence of vector-borne diseases, we lack sampling methods that are both practical and reliable. Here we illustrated how comprehensive patterns can be revealed from observational data by applying path analysis and model selection approaches and combining cross-sectional and longitudinal analyses. By employing this combined approach on blood-associated parasites, we were able to distinguish between direct and indirect effects and to predict the causal relationships between host-related characteristics and the parasite composition over time and space. We concluded that direct interactions within the community play only a minor role in determining community composition relative to host characteristics and the life history of the community members.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Argentina 1 1%
Unknown 72 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 24%
Student > Ph. D. Student 12 16%
Student > Master 12 16%
Student > Bachelor 7 9%
Student > Doctoral Student 3 4%
Other 11 15%
Unknown 11 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 39%
Immunology and Microbiology 7 9%
Environmental Science 5 7%
Veterinary Science and Veterinary Medicine 4 5%
Biochemistry, Genetics and Molecular Biology 4 5%
Other 10 14%
Unknown 15 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 August 2015.
All research outputs
#20,288,585
of 22,824,164 outputs
Outputs from Parasites & Vectors
#4,846
of 5,463 outputs
Outputs of similar age
#223,252
of 266,176 outputs
Outputs of similar age from Parasites & Vectors
#99
of 124 outputs
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So far Altmetric has tracked 5,463 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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